Triple
T1831430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fedora Kinoite |
E40768
|
entity |
| Predicate | applicationDeliveryModel |
P1486
|
FINISHED |
| Object | Flatpak for graphical applications |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Flatpak for graphical applications | Statement: [Fedora Kinoite, applicationDeliveryModel, Flatpak for graphical applications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: applicationDeliveryModel Context triple: [Fedora Kinoite, applicationDeliveryModel, Flatpak for graphical applications]
-
A.
deploymentModel
Indicates the type or manner in which a system, service, or resource is deployed or made available (e.g., on-premises, cloud, hybrid).
-
B.
operatingModel
Indicates how an organization structures and manages its processes, resources, and governance to deliver its products or services.
-
C.
deploymentType
Indicates the manner or configuration in which a system, application, or component is deployed or made operational.
-
D.
distributionMethod
chosen
Indicates the means or channel through which something (such as a product, resource, or information) is delivered or made available to recipients.
-
E.
softwareModel
Indicates that one entity serves as a software-based representation or abstraction (a model) of another entity or system.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a8864644bc8190b2358ab897194ac1 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb45402688190b9a535b14030c354 |
completed | March 7, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69abafd6a9948190ac2b2743db6f8f69 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:32 p.m.